DocumentCode :
2559798
Title :
Unscented Particle Filter algorithm based on artificial fish swarm algorithm
Author :
Tian, Yu-min ; Chen, Li
Author_Institution :
Res. Inst. of Comput. Peripherals, Xidian Univ., Xi´´an, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1123
Lastpage :
1126
Abstract :
Aiming at the problem of Unscented Particle Filter (UPF) algorithm such as particles degeneracy and particles impoverishment, by use of the behaviors of preying, swarming and following in the artificial fish swarm algorithm, an artificial fish swarm algorithm is used to make the particles of UKF move toward the global optimum, which optimalizes the resampling process and relieves the problem of particles degeneracy and impoverishment. Experiments show that this algorithm improves the estimation accuracy of UPF algorithm.
Keywords :
Kalman filters; particle filtering (numerical methods); particle swarm optimisation; UKF; artificial fish swarm algorithm; particles degeneracy; particles impoverishment; preying behavior; resampling process optimisation; swarming behavior; unscented Kalman filter; unscented particle filter algorithm; Algorithm design and analysis; Fellows; Filtering algorithms; Marine animals; Particle filters; Signal processing algorithms; Artificial Fish Swarm Algorithm; Unscented Particle Filter; particles impoverishment; resampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234707
Filename :
6234707
Link To Document :
بازگشت